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dc.contributorMulti-disciplinary Studiesen_US
dc.contributorDepartment of Electronic and Information Engineeringen_US
dc.creatorChan, Chong-fun-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/3892-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleSoft decision decoding using neural networksen_US
dcterms.abstractThe advantage of soft decision decoding over the hard decision decoding is well known. Soft decision decoding of convolutional codes using Viterbi algorithm has low complexity, but it is not true for block codes. The neural network is used to aid the implementation of soft decision decoder of block codes. The concept and algorithm for training a network is presented. In this dissertation, a decoder which first implements the hard decision decoding of block codes, second, a procedure (called Decision Maker) tests to see if that result matches the result of soft decision decoding and third the neural network is used to implement the soft decision decoding if a match is not found. The advantage of the test procedure is that if the hard decision decoding result is good enough then the computation effort is greatly reduced. The generalization capability and storage capability of neural network are exploited to aid the soft decision decoder of block codes. Backpropagation networks are successfully trained for the binary Hamming (7,4) code and (9,5) code. Simulation results show that the performance of the decoder with Decision Maker and neural network approaches that of the maximum likelihood decoder over a wide range of signal to noise rations.en_US
dcterms.extentv, 92 leaves : ill. ; 30 cmen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2000en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHCoding theoryen_US
dcterms.LCSHDecoders (Electronics)en_US
dcterms.LCSHNeural networks (Computer science)en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/3892